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Introduction to Programming with Fortran: With Coverage of Fortran 90, 95, 2003, 2008 and 77

by Ian Chivers Jane Sleightholme

This edition has been revised to stress the use of modern Fortran throughout: Key features: lots of clear, simple and complete examples highlighting the, core language features of modern Fortran including data typing, array processing, control structures functions, subroutines, user defined types and pointers, pinpoints common problems that occur when programming, has sample output from a variety of compilers, expands on the first edition, by introducing modules as soon as the fundamental language features have been covered. Modules are the major organisational feature of Fortran and are the equivalent of classes in other languages, major new features covered in this edition include, introduction to object oriented programming in Fortran introduction to parallel programming in Fortran using MPI, OpenMP and Coarray Fortra, this edition has three target audiences the complete beginner existing Fortran programmers wishing to update their code those with programming experience in other languagesIan Chivers and Jane Sleightholme are the joint owners of comp-fortran-90 which is a lively forum for the exchange of technical details of the Fortran language. Ian is the editor of the ACM Fortran Forum and both Jane and Ian have both been involved in the Fortran standardisation process. The authors have been teaching and supporting Fortran and related areas for over 30 years and their latest book reflects the lessons that have been learnt from this.

Introduction to Programming with Fortran

by Jane Sleightholme Ian Chivers

This edition has been revised to stress the use of modern Fortran throughout: Key features: lots of clear, simple and complete examples highlighting the, core language features of modern Fortran including data typing, array processing, control structures functions, subroutines, user defined types and pointers, pinpoints common problems that occur when programming, has sample output from a variety of compilers, expands on the first edition, by introducing modules as soon as the fundamental language features have been covered. Modules are the major organisational feature of Fortran and are the equivalent of classes in other languages, major new features covered in this edition include, introduction to object oriented programming in Fortran introduction to parallel programming in Fortran using MPI, OpenMP and Coarray Fortra, this edition has three target audiences the complete beginner existing Fortran programmers wishing to update their code those with programming experience in other languages Ian Chivers and Jane Sleightholme are the joint owners of comp-fortran-90 which is a lively forum for the exchange of technical details of the Fortran language. Ian is the editor of the ACM Fortran Forum and both Jane and Ian have both been involved in the Fortran standardisation process. The authors have been teaching and supporting Fortran and related areas for over 30 years and their latest book reflects the lessons that have been learnt from this.

Introduction to Programming with Fortran: With Coverage Of Fortran 90, 95, 2003, 2008 And 77

by Jane Sleightholme Ian Chivers

This fourth Edition presents new examples on submodules, derived type i/o, object oriented programming, abstract interfaces and procedure pointers, C interop, sorting and searching, statistics and converting to more modern versions of Fortran.Key FeaturesHighlights the core language features of modern Fortran including data typing, array processing, control structures, functions, subroutines, modules and submodules, user defined types, pointers, operator overloading, generic programming, parallel programming, abstract interfaces, procedure pointersPinpoints common problems that occur when programmingIllustrates the use of several compilersIntroduction to Programming with Fortran has been written for the complete beginner with little or no programming background as well as existing Fortran programmers and those with programming experience in other languages

Introduction to Programming With Greenfoot: Object-Oriented Programming in Java With Games and Simulations

by Michael Kölling

Introduction to Programming with Greenfoot: Object-Oriented Programming in Java with games and Simulations is ideal for introductory courses in Java Programming or Introduction to Computer Science. The only textbook to teach Java programming using Greenfoot--this is "Serious Fun. " Programming doesn't have to be dry and boring. This book teaches Java programming in an interactive and engaging way that is technically relevant, pedagogically sound, and highly motivational for students. Using the Greenfoot environment, and an extensive collection of compelling example projects, students are given a unique, graphical framework in which to learn programming.

An Introduction to Project Management

by Kathy Schwalbe

The fifth edition of An Introduction to Project Management provides a separate chapter for planning integration and scope management and for planning time and cost management. Additional examples are provided for creating work breakdown structures and schedules. It also includes information on Basecamp, a free web-based project management tool, along with a user guide (replaces AtTask in Appendix B). In addition to updating many references and examples, this edition continues to include several popular features: - Follows the Project Management Institute's PMBOK® Guide, Fifth Edition (2013) - Has chapters for each process group and a comprehensive case study to illustrate applying tools and techniques throughout the project life cycle - Includes a Guide for using Microsoft Project 2013 - Provides a free trial of MatchWare's MindView Business software (www.matchware.com/intropm), a tool for creating mind maps, Gantt charts, and other project documents - Uses real-world examples and references, including opening cases and case wrap-ups, examples of what went right, what went wrong, media snapshots, best practices, and video highlights in each chapter - End of chapter materials include chapter summaries, quick quizzes, discussion questions, and exercises, with case studies provided in Appendix C -Comprehensive, secure instructor site available with lecture slides, solution files, test banks, etc. -Free Web site includes over fifty template files, online quizzes and games, data files for Project 2013, links to sites mentioned in the text, and much more.

Introduction to Property Testing

by Oded Goldreich

Property testing is concerned with the design of super-fast algorithms for the structural analysis of large quantities of data. The aim is to unveil global features of the data, such as determining whether the data has a particular property or estimating global parameters. Remarkably, it is possible for decisions to be made by accessing only a small portion of the data. Property testing focuses on properties and parameters that go beyond simple statistics. This book provides an extensive and authoritative introduction to property testing. It provides a wide range of algorithmic techniques for the design and analysis of tests for algebraic properties, properties of Boolean functions, graph properties, and properties of distributions.

An Introduction to Python and Computer Programming (Lecture Notes in Electrical Engineering #353)

by Yue Zhang

This book introduces Python programming language and fundamental concepts in algorithms and computing. Its target audience includes students and engineers with little or no background in programming, who need to master a practical programming language and learn the basic thinking in computer science/programming. The main contents come from lecture notes for engineering students from all disciplines, and has received high ratings. Its materials and ordering have been adjusted repeatedly according to classroom reception. Compared to alternative textbooks in the market, this book introduces the underlying Python implementation of number, string, list, tuple, dict, function, class, instance and module objects in a consistent and easy-to-understand way, making assignment, function definition, function call, mutability and binding environments understandable inside-out. By giving the abstraction of implementation mechanisms, this book builds a solid understanding of the Python programming language.

Introduction to Python for Humanists (Chapman & Hall/CRC The Python Series)

by William Mattingly

This book will introduce digital humanists at all levels of education to Python. It provides background and guidance on learning the Python computer programming language, and as it presumes no knowledge on the part of the reader about computers or coding concepts allows the reader to gradually learn the more complex tasks that are currently popular in the field of digital humanities. This book will be aimed at undergraduates, graduates, and faculty who are interested in learning how to use Python as a tool within their workflow. An Introduction to Python for Digital Humanists will act as a primer for students who wish to use Python, allowing them to engage with more advanced textbooks. This book fills a real need, as it is first Python introduction to be aimed squarely at humanities students, as other books currently available do not approach Python from a humanities perspective. It will be designed so that those experienced in Python can teach from it, in addition to allowing those who are interested in being self-taught can use it for that purpose.Key Features: Data analysis Data science Computational humanities Digital humanities Python Natural language processing Social network analysis App development

Introduction to Python for Kids: Learn Python the Fun Way by Completing Activities and Solving Puzzles

by Aarthi Elumalai

Want to create cool games and apps to impress your friends (or yourself), but not sure where to start? Or, have you tried your hand at programming, but got utterly bored after combing through hundreds of pages of dry text? Then you’ve come to the right place! This book is the perfect blend of education and fun for kids 8 years and above looking to learn the magic of Python, one of the easiest and most powerful programming languages around, all while solving fun puzzles and building your own projects on the way. Yes, there’ll be chapters on the fundamentals of Python, such as variables, numbers, strings, automation with conditions, loops and functions, objects, and files. But, early on in the book you’ll get started with Turtle, a Python package that was custom-made for kids like you. It lets you literally draw and animate on your computer! Every concept will be interspersed with a fun mini project with Turtle, so you’ll never get bored. Once you get the fundamentals down, you’ll dive right into Tkinter and Pygame, more fun Python packages (goodbye theory!) and you’ll learn all about creating apps and games like the ones you see and use every day (bouncing ball, temperature converter, calculator, rock-paper-scissors, and so much more!). There are also four capstone projects at the end of the book that convert everything you’ve learned so far into full-blown apps and games that you can show off to your friends, parents, and even teachers! You’ll be creating a snake game with Turtle, a tic tac toe game with Tkinter, a full-fledged paint app, again with Tkinter, and finally, a classic space shooters game with Pygame (the cherry on top). Every project chapter will be accompanied with the logic behind the game/app and an explanation on how you’ve arrived at the logic. You’ll develop strong problem solving skills that’ll help you create future projects on your own. There are also two chapters dedicated to just creating fun mini projects and puzzles, one of them placed in the middle of the book to give you a welcome break from all the learning. The book ends with an overview on web development with Python and ideas for more fun projects and puzzles you can solve on your own. Become the “most likely to succeed” kid in your grade while having the most fun getting there! What You'll Learn Gain a gentle, but thorough introduction into the world of programming and Python Create programs and solve problems with core Python concepts Build mini projects and capstone projects (showcase worthy) with Turtle, Tkinter, and Pygame Develop programming skills while doing the puzzles and activities described in the book Who This Book Is ForKids 8 years and above.

Introduction to Python for Science and Engineering (Series in Computational Physics)

by David Pine

This guide offers a quick and incisive introduction to Python programming for anyone. The author has carefully developed a concise approach to using Python in any discipline of science and engineering, with plenty of examples, practical hints, and insider tips. <p><p>Readers will see why Python is such a widely appealing program, and learn the basics of syntax, data structures, input and output, plotting, conditionals and loops, user-defined functions, curve fitting, numerical routines, animation, and visualization. The author teaches by example and assumes no programming background for the reader. <p><p>David J. Pine is the Silver Professor and Professor of Physics at New York University, and Chair of the Department of Chemical and Biomolecular Engineering at the NYU Tandon School of Engineering. He is an elected fellow of the American Physical Society and American Association for the Advancement of Science (AAAS), and is a Guggenheim Fellow.

Introduction to Python in Earth Science Data Analysis: From Descriptive Statistics to Machine Learning (Springer Textbooks in Earth Sciences, Geography and Environment)

by Maurizio Petrelli

This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.

Introduction to Python Network Automation: The First Journey

by Brendan Choi

Learn and implement network automation within the Enterprise network using Python 3. This introductory book will be your guide to building an integrated virtual networking lab to begin your Network Automation journey and master the basics of Python Network Automation. The book features a review of the practical Python network automation scripting skills and tips learned from the production network, so you can safely test and practice in a lab environment first, various Python modules such as paramiko and netmiko, pandas, re, and much more. You'll also develop essential skills such as Python scripting, regular expressions, Linux and Windows administration, VMware virtualization, and Cisco networking from the comfort of your laptop/PC with no actual networking hardware. Finally, you will learn to write a fully automated and working Cisco IOS XE upgrade application using Python.Introduction to Python Network Automation uses a canonical order, where you begin at the bottom and by the time you have completed this book, you will at least reach the intermediate level of Python coding for enterprise networking automation using native Python tools. What You'll Learn Build a proper GNS3-based networking lab for Python network automation needsWrite the basics of Python code in both the Windows and Linux environmentsControl network devices using telnet, SSH, and SNMP protocols using Python codesUnderstand virtualization and how to use VMware workstationExamine virtualization and how to use VMware Workstation ProDevelop a working Cisco IOS upgrade application Who This Book Is For IT engineers and developers, network managers and students, who would like to learn network automation using Python.

Introduction to Python Programming

by Gowrishankar S Veena A

Introduction to Python Programming is written for students who are beginners in the field of computer programming. This book presents an intuitive approach to the concepts of Python Programming for students. This book differs from traditional texts not only in its philosophy but also in its overall focus, level of activities, development of topics, and attention to programming details. The contents of the book are chosen with utmost care after analyzing the syllabus for Python course prescribed by various top universities in USA, Europe, and Asia. Since the prerequisite know-how varies significantly from student to student, the book’s overall overture addresses the challenges of teaching and learning of students which is fine-tuned by the authors’ experience with large sections of students. This book uses natural language expressions instead of the traditional shortened words of the programming world. This book has been written with the goal to provide students with a textbook that can be easily understood and to make a connection between what students are learning and how they may apply that knowledge. <P><P> Features of this book <P><P> This book does not assume any previous programming experience, although of course, any exposure to other programming languages is useful <P><P> This book introduces all of the key concepts of Python programming language with helpful illustrations <P><P> Programming examples are presented in a clear and consistent manner <P><P> Each line of code is numbered and explained in detail <P><P> Use of f-strings throughout the book <P><P> Hundreds of real-world examples are included and they come from fields such as entertainment, sports, music and environmental studies <P><P> Students can periodically check their progress with in-chapter quizzes that appear in all chapters

Introduction to Quantum Algorithms via Linear Algebra, second edition

by Richard J. Lipton Kenneth W. Regan

Quantum computing explained in terms of elementary linear algebra, emphasizing computation and algorithms and requiring no background in physics.This introduction to quantum algorithms is concise but comprehensive, covering many key algorithms. It is mathematically rigorous but requires minimal background and assumes no knowledge of quantum theory or quantum mechanics. The book explains quantum computation in terms of elementary linear algebra; it assumes the reader will have some familiarity with vectors, matrices, and their basic properties, but offers a review of the relevant material from linear algebra. By emphasizing computation and algorithms rather than physics, it makes quantum algorithms accessible to students and researchers in computer science who have not taken courses in quantum physics or delved into fine details of quantum effects, apparatus, circuits, or theory.

Introduction to Quantum Computing (The Materials Research Society Series)

by Ray LaPierre

This book provides a self-contained undergraduate course on quantum computing based on classroom-tested lecture notes. It reviews the fundamentals of quantum mechanics from the double-slit experiment to entanglement, before progressing to the basics of qubits, quantum gates, quantum circuits, quantum key distribution, and some of the famous quantum algorithms. As well as covering quantum gates in depth, it also describes promising platforms for their physical implementation, along with error correction, and topological quantum computing. With quantum computing expanding rapidly in the private sector, understanding quantum computing has never been so important for graduates entering the workplace or PhD programs. Assuming minimal background knowledge, this book is highly accessible, with rigorous step-by-step explanations of the principles behind quantum computation, further reading, and end-of-chapter exercises, ensuring that undergraduate students in physics and engineering emerge well prepared for the future.

Introduction to Quantum Computing: From a Layperson to a Programmer in 30 Steps

by Hiu Yung Wong

This textbook introduces quantum computing to readers who do not have much background in linear algebra. The author targets undergraduate and master students, as well as non-CS and non-EE students who are willing to spend about 60 -90 hours seriously learning quantum computing. Readers will be able to write their program to simulate quantum computing algorithms and run on real quantum computers on IBM-Q. Moreover, unlike the books that only give superficial, “hand-waving” explanations, this book uses exact formalism so readers can continue to pursue more advanced topics based on what they learn from this book.Encourages students to embrace uncertainty over the daily classical experience, when encountering quantum phenomena;Uses narrative to start each section with analogies that help students to grasp the critical concept quickly;Uses numerical substitutions, accompanied by Python programming and IBM-Q quantum computer programming, as examples in teaching all critical concepts.

Introduction to Quantum Computing: From a Layperson to a Programmer in 30 Steps

by Hiu Yung Wong

This textbook introduces quantum computing to readers who do not have much background in linear algebra based on the self-study experience of the author as an engineer. The author targets undergraduate and master students who are willing to spend about 60 -90 hours seriously learning quantum computing. This book is also suitable for self-study and teaching videos for each chapter and more than 200 exercises with answers are provided. Readers will be able to write their program to simulate quantum computing algorithms and run on real quantum computers on IBM-Q. Moreover, unlike books that only give superficial, “hand-waving” explanations, this book uses exact formalism so readers can continue to pursue more advanced topics based on what they learn from this book

Introduction to Quantum Information Science

by Masahito Hayashi Satoshi Ishizaka Akinori Kawachi Gen Kimura Tomohiro Ogawa

This book presents the basics of quantum information, e. g. , foundation of quantum theory, quantum algorithms, quantum entanglement, quantum entropies, quantum coding, quantum error correction and quantum cryptography. The required knowledge is only elementary calculus and linear algebra. This way the book can be understood by undergraduate students. In order to study quantum information, one usually has to study the foundation of quantum theory. This book describes it from more an operational viewpoint which is suitable for quantum information while traditional textbooks of quantum theory lack this viewpoint. The current book bases on Shor's algorithm, Grover's algorithm, Deutsch-Jozsa's algorithm as basic algorithms. To treat several topics in quantum information, this book covers several kinds of information quantities in quantum systems including von Neumann entropy. The limits of several kinds of quantum information processing are given. As important quantum protocols, this book contains quantum teleportation, quantum dense coding, quantum data compression. In particular conversion theory of entanglement via local operation and classical communication are treated too. This theory provides the quantification of entanglement, which coincides with von Neumann entropy. The next part treats the quantum hypothesis testing. The decision problem of two candidates of the unknown state are given. The asymptotic performance of this problem is characterized by information quantities. Using this result, the optimal performance of classical information transmission via noisy quantum channel is derived. Quantum information transmission via noisy quantum channel by quantum error correction are discussed too. Based on this topic, the secure quantum communication is explained. In particular, the quantification of quantum security which has not been treated in existing book is explained. This book treats quantum cryptography from a more practical viewpoint.

An Introduction to Quantum Spin Systems (Lecture Notes in Physics #816)

by Damian J. Farnell John B. Parkinson

The topic of lattice quantum spin systems is a fascinating and by now well-established branch of theoretical physics. However, many important questions remain to be answered. Their intrinsically quantum mechanical nature and the large (usually effectively infinite) number of spins in macroscopic materials often leads to unexpected or counter-intuitive results and insights. Spin systems are not only the basic models for a whole host of magnetic materials but they are also important as prototypical models of quantum systems. Low dimensional systems (as treated in this primer), in 2D and especially 1D, have been particularly fruitful because their simplicity has enabled exact solutions to be determined in many cases. These exact solutions contain many highly nontrivial features. This book was inspired by a set of lectures on quantum spin systems and it is set at a level of practical detail that is missing in other textbooks in the area. It will guide the reader through the foundations of the field. In particular, the solutions of the Heisenberg and XY models at zero temperature using the Bethe Ansatz and the Jordan-Wigner transformation are covered in some detail. The use of approximate methods, both theoretical and numerical, to tackle more advanced topics is considered. The final chapter describes some very recent applications of approximate methods in order to show some of the directions in which the study of these systems is currently developing.

An Introduction to Quasisymmetric Schur Functions: Hopf Algebras, Quasisymmetric Functions, and Young Composition Tableaux (SpringerBriefs in Mathematics)

by Kurt Luoto Stephanie Van Willigenburg Stefan Mykytiuk

An Introduction to Quasisymmetric Schur Functions is aimed at researchers and graduate students in algebraic combinatorics. This book introduces readers to the algebra of quasisymmetric functions and its fundamental theory. Results and relevant new contributions are included which pertains to the dynamic new basis of quasisymmetric Schur functions. A state-of-the-art summary is included with respect to an exciting new basis of algebra, which is the basis of quasisymmetric Schur functions, whose combinatorics is analogous to that of the renowned Schur functions.

Introduction to Queueing Networks: Theory ∩ Practice (Springer Series in Operations Research and Financial Engineering)

by J. MacGregor Smith

The book examines the performance and optimization of systems where queueing and congestion are important constructs. Both finite and infinite queueing systems are examined. Many examples and case studies are utilized to indicate the breadth and depth of the queueing systems and their range of applicability. Blocking of these processes is very important and the book shows how to deal with this problem in an effective way and not only compute the performance measures of throughput, cycle times, and WIP but also to optimize the resources within these systems. The book is aimed at advanced undergraduate, graduate, and professionals and academics interested in network design, queueing performance models and their optimization. It assumes that the audience is fairly sophisticated in their mathematical understanding, although the explanations of the topics within the book are fairly detailed.

Introduction to Queueing Systems with Telecommunication Applications

by László Lakatos László Szeidl Miklós Telek

The book is the extended and revised version of the 1st edition and is composed of two main parts: mathematical background and queueing systems with applications. The mathematical background is a self-containing introduction to the stochastic processes of the later studied queueing systems. It starts with a quick introduction to probability theory and stochastic processes and continues with chapters on Markov chains and regenerative processes. More recent advances of queueing systems are based on phase type distributions, Markov arrival processes and quasy birth death processes, which are introduced in the last chapter of the first part.The second part is devoted to queueing models and their applications. After the introduction of the basic Markovian (from M/M/1 to M/M/1//N) and non-Markovian (M/G/1, G/M/1) queueing systems, a chapter presents the analysis of queues with phase type distributions, Markov arrival processes (from PH/M/1 to MAP/PH/1/K). The next chapter presents the classical queueing network results and the rest of this part is devoted to the application examples. There are queueing models for bandwidth charing with different traffic classes, slotted multiplexers, media access protocols like Aloha and IEEE 802.11b, priority systems and retrial systems.An appendix supplements the technical content with Laplace and z transformation rules, Bessel functions and a list of notations. The book contains examples and exercises throughout and could be used for graduate students in engineering, mathematics and sciences.Reviews of first edition:"The organization of the book is such that queueing models are viewed as special cases of more general stochastic processes, such as birth-death or semi-Markov processes. … this book is a valuable addition to the queuing literature and provides instructors with a viable alternative for a textbook to be used in a one- or two-semester course on queueing models, at the upper undergraduate or beginning graduate levels."Charles Knessl, SIAM Review, Vol. 56 (1), March, 2014

Introduction to Queueing Systems with Telecommunication Applications

by Laszlo Lakatos Miklos Telek Laszlo Szeidl

The book is composed of two main parts: mathematical background and queueing systems with applications. The mathematical background is a self containing introduction to the stochastic processes of the later studies queueing systems. It starts with a quick introduction to probability theory and stochastic processes and continues with chapters on Markov chains and regenerative processes. More recent advances of queueing systems are based on phase type distributions, Markov arrival processes and quasy birth death processes, which are introduced in the last chapter of the first part. The second part is devoted to queueing models and their applications. After the introduction of the basic Markovian (from M/M/1 to M/M/1//N) and non-Markovian (M/G/1, G/M/1) queueing systems, a chapter presents the analysis of queues with phase type distributions, Markov arrival processes (from PH/M/1 to MAP/PH/1/K). The next chapter presents the classical queueing network results and the rest of this part is devoted to the application examples. There are queueing models for bandwidth charing with different traffic classes, slotted multiplexers, ATM switches, media access protocols like Aloha and IEEE 802.11b, priority systems and retrial systems. An appendix supplements the technical content with Laplace and z transformation rules, Bessel functions and a list of notations. The book contains examples and exercises throughout and could be used for graduate students in engineering, mathematics and sciences.

Introduction to R for Business Intelligence

by Jay Gendron

Learn how to leverage the power of R for Business Intelligence About This Book * Use this easy-to-follow guide to leverage the power of R analytics and make your business data more insightful. * This highly practical guide teaches you how to develop dashboards that help you make informed decisions using R. * Learn the A to Z of working with data for Business Intelligence with the help of this comprehensive guide. Who This Book Is For This book is for data analysts, business analysts, data science professionals or anyone who wants to learn analytic approaches to business problems. Basic familiarity with R is expected. What You Will Learn * Extract, clean, and transform data * Validate the quality of the data and variables in datasets * Learn exploratory data analysis * Build regression models * Implement popular data-mining algorithms * Visualize results using popular graphs * Publish the results as a dashboard through Interactive Web Application frameworks In Detail Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance. In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards. After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence. Style and approach This book will take a step-by-step approach and instruct you in how you can achieve Business Intelligence from scratch using R. We will start with extracting data and then move towards exploring, analyzing, and visualizing it. Eventually, you will learn how to create insightful dashboards that help you make informed decisions--and all of this with the help of real-life examples.

An Introduction to R for Quantitative Economics: Graphing, Simulating and Computing (SpringerBriefs in Economics)

by Vikram Dayal

This book gives an introduction to R to build up graphing, simulating and computing skills to enable one to see theoretical and statistical models in economics in a unified way. The great advantage of R is that it is free, extremely flexible and extensible. The book addresses the specific needs of economists, and helps them move up the R learning curve. It covers some mathematical topics such as, graphing the Cobb-Douglas function, using R to study the Solow growth model, in addition to statistical topics, from drawing statistical graphs to doing linear and logistic regression. It uses data that can be downloaded from the internet, and which is also available in different R packages. With some treatment of basic econometrics, the book discusses quantitative economics broadly and simply, looking at models in the light of data. Students of economics or economists keen to learn how to use R would find this book very useful.

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